Machine Learning & Compilers

0d2bf4a55ccf5ca212897c2c09e18c94?s=47 Chris Cummins
September 09, 2016

Machine Learning & Compilers

Predictive modeling using machine learning is an effective method for building compiler heuristics, but there is a shortage of benchmarks. Typical machine learning experiments outside of the compilation field train over thousands or millions of examples. In machine learning for compilers, however, there are typically only a few dozen common benchmarks available. This limits the quality of learned models, as they have very sparse training data for what are often high-dimensional feature spaces.

In this talk I present CLgen, a tool for generating benchmarks for predictive modeling.


Chris Cummins

September 09, 2016